Handling imbalanced data in intrusion detection systems using generative adversarial networks
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In this paper, we propose a novel solution to this problem by using generative adversarial networks to generate synthesized attack data for IDS. The synthesized attacks are merged with the original data to form the augmented dataset. Three popular machine learning techniques are trained on the augmented dataset.
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Handling imbalanced data in intrusion detection systems using generative adversarial networks
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Handling imbalanced data in intrusion detection systems using generative adversarial networks
Tìm kiếm theo từ khóa liên quan:
Handling imbalanced data Intrusion detection systems Generative adversarial networks Machine learning-based intrusion detection Imbalanced datasetGợi ý tài liệu liên quan:
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